SNP-based mate allocation strategies to maximize total genetic value in pigs

Abstract Background Mate allocation strategies that account for non-additive genetic effects can be used to maximize the overall genetic merit of future offspring. Accounting for dominance effects in genetic evaluations is easier in a genomic context, than in a classical pedigree-based context becau...

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Main Authors: David González-Diéguez, Llibertat Tusell, Céline Carillier-Jacquin, Alban Bouquet, Zulma G. Vitezica
Format: Article
Language:deu
Published: BMC 2019-09-01
Series:Genetics Selection Evolution
Online Access:http://link.springer.com/article/10.1186/s12711-019-0498-y
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spelling doaj-856d5428ecef41bc889bf3679f8c5bfe2020-11-25T02:50:12ZdeuBMCGenetics Selection Evolution1297-96862019-09-0151111010.1186/s12711-019-0498-ySNP-based mate allocation strategies to maximize total genetic value in pigsDavid González-Diéguez0Llibertat Tusell1Céline Carillier-Jacquin2Alban Bouquet3Zulma G. Vitezica4GenPhySE, INRA, Université de ToulouseGenPhySE, INRA, Université de ToulouseGenPhySE, INRA, Université de ToulouseIFIP Institut du PorcGenPhySE, INRA, Université de ToulouseAbstract Background Mate allocation strategies that account for non-additive genetic effects can be used to maximize the overall genetic merit of future offspring. Accounting for dominance effects in genetic evaluations is easier in a genomic context, than in a classical pedigree-based context because the combinations of alleles at loci are known. The objective of our study was two-fold. First, dominance variance components were estimated for age at 100 kg (AGE), backfat depth (BD) at 140 days, and for average piglet weight at birth within litter (APWL). Second, the efficiency of mate allocation strategies that account for dominance and inbreeding depression to maximize the overall genetic merit of future offspring was explored. Results Genetic variance components were estimated using genomic models that included inbreeding depression with and without non-additive genetic effects (dominance). Models that included dominance effects did not fit the data better than the genomic additive model. Estimates of dominance variances, expressed as a percentage of additive genetic variance, were 20, 11, and 12% for AGE, BD, and APWL, respectively. Estimates of additive and dominance single nucleotide polymorphism effects were retrieved from the genetic variance component estimates and used to predict the outcome of matings in terms of total genetic and breeding values. Maximizing total genetic values instead of breeding values in matings gave the progeny an average advantage of − 0.79 days, − 0.04 mm, and 11.3 g for AGE, BD and APWL, respectively, but slightly reduced the expected additive genetic gain, e.g. by 1.8% for AGE. Conclusions Genomic mate allocation accounting for non-additive genetic effects is a feasible and potential strategy to improve the performance of the offspring without dramatically compromising additive genetic gain.http://link.springer.com/article/10.1186/s12711-019-0498-y
collection DOAJ
language deu
format Article
sources DOAJ
author David González-Diéguez
Llibertat Tusell
Céline Carillier-Jacquin
Alban Bouquet
Zulma G. Vitezica
spellingShingle David González-Diéguez
Llibertat Tusell
Céline Carillier-Jacquin
Alban Bouquet
Zulma G. Vitezica
SNP-based mate allocation strategies to maximize total genetic value in pigs
Genetics Selection Evolution
author_facet David González-Diéguez
Llibertat Tusell
Céline Carillier-Jacquin
Alban Bouquet
Zulma G. Vitezica
author_sort David González-Diéguez
title SNP-based mate allocation strategies to maximize total genetic value in pigs
title_short SNP-based mate allocation strategies to maximize total genetic value in pigs
title_full SNP-based mate allocation strategies to maximize total genetic value in pigs
title_fullStr SNP-based mate allocation strategies to maximize total genetic value in pigs
title_full_unstemmed SNP-based mate allocation strategies to maximize total genetic value in pigs
title_sort snp-based mate allocation strategies to maximize total genetic value in pigs
publisher BMC
series Genetics Selection Evolution
issn 1297-9686
publishDate 2019-09-01
description Abstract Background Mate allocation strategies that account for non-additive genetic effects can be used to maximize the overall genetic merit of future offspring. Accounting for dominance effects in genetic evaluations is easier in a genomic context, than in a classical pedigree-based context because the combinations of alleles at loci are known. The objective of our study was two-fold. First, dominance variance components were estimated for age at 100 kg (AGE), backfat depth (BD) at 140 days, and for average piglet weight at birth within litter (APWL). Second, the efficiency of mate allocation strategies that account for dominance and inbreeding depression to maximize the overall genetic merit of future offspring was explored. Results Genetic variance components were estimated using genomic models that included inbreeding depression with and without non-additive genetic effects (dominance). Models that included dominance effects did not fit the data better than the genomic additive model. Estimates of dominance variances, expressed as a percentage of additive genetic variance, were 20, 11, and 12% for AGE, BD, and APWL, respectively. Estimates of additive and dominance single nucleotide polymorphism effects were retrieved from the genetic variance component estimates and used to predict the outcome of matings in terms of total genetic and breeding values. Maximizing total genetic values instead of breeding values in matings gave the progeny an average advantage of − 0.79 days, − 0.04 mm, and 11.3 g for AGE, BD and APWL, respectively, but slightly reduced the expected additive genetic gain, e.g. by 1.8% for AGE. Conclusions Genomic mate allocation accounting for non-additive genetic effects is a feasible and potential strategy to improve the performance of the offspring without dramatically compromising additive genetic gain.
url http://link.springer.com/article/10.1186/s12711-019-0498-y
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